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Single-nucleotide polymorphism-gene intermixed networking reveals co-linkers connected to multiple gene expression phenotypes
Gene expression profiles and single-nucleotide polymorphism (SNP) profiles are modern data for genetic analysis. It is possible to use the two types of information to analyze the relationships among genes by some genetical genomics approaches. In this study, gene expression profiles were used as exp...
Autores principales: | , , , , , , , , , , |
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Formato: | Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2007
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2359868/ https://www.ncbi.nlm.nih.gov/pubmed/18466544 |
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author | Gong, Bin-Sheng Zhang, Qing-Pu Zhang, Guang-Mei Zhang, Shao-Jun Zhang, Wei Lv, Hong-Chao Zhang, Fan Lv, Sa-Li Li, Chuan-Xing Rao, Shao-Qi Li, Xia |
author_facet | Gong, Bin-Sheng Zhang, Qing-Pu Zhang, Guang-Mei Zhang, Shao-Jun Zhang, Wei Lv, Hong-Chao Zhang, Fan Lv, Sa-Li Li, Chuan-Xing Rao, Shao-Qi Li, Xia |
author_sort | Gong, Bin-Sheng |
collection | PubMed |
description | Gene expression profiles and single-nucleotide polymorphism (SNP) profiles are modern data for genetic analysis. It is possible to use the two types of information to analyze the relationships among genes by some genetical genomics approaches. In this study, gene expression profiles were used as expression traits. And relationships among the genes, which were co-linked to a common SNP(s), were identified by integrating the two types of information. Further research on the co-expressions among the co-linked genes was carried out after the gene-SNP relationships were established using the Haseman-Elston sib-pair regression. The results showed that the co-expressions among the co-linked genes were significantly higher if the number of connections between the genes and a SNP(s) was more than six. Then, the genes were interconnected via one or more SNP co-linkers to construct a gene-SNP intermixed network. The genes sharing more SNPs tended to have a stronger correlation. Finally, a gene-gene network was constructed with their intensities of relationships (the number of SNP co-linkers shared) as the weights for the edges. |
format | Text |
id | pubmed-2359868 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2007 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-23598682008-05-06 Single-nucleotide polymorphism-gene intermixed networking reveals co-linkers connected to multiple gene expression phenotypes Gong, Bin-Sheng Zhang, Qing-Pu Zhang, Guang-Mei Zhang, Shao-Jun Zhang, Wei Lv, Hong-Chao Zhang, Fan Lv, Sa-Li Li, Chuan-Xing Rao, Shao-Qi Li, Xia BMC Proc Proceedings Gene expression profiles and single-nucleotide polymorphism (SNP) profiles are modern data for genetic analysis. It is possible to use the two types of information to analyze the relationships among genes by some genetical genomics approaches. In this study, gene expression profiles were used as expression traits. And relationships among the genes, which were co-linked to a common SNP(s), were identified by integrating the two types of information. Further research on the co-expressions among the co-linked genes was carried out after the gene-SNP relationships were established using the Haseman-Elston sib-pair regression. The results showed that the co-expressions among the co-linked genes were significantly higher if the number of connections between the genes and a SNP(s) was more than six. Then, the genes were interconnected via one or more SNP co-linkers to construct a gene-SNP intermixed network. The genes sharing more SNPs tended to have a stronger correlation. Finally, a gene-gene network was constructed with their intensities of relationships (the number of SNP co-linkers shared) as the weights for the edges. BioMed Central 2007-12-18 /pmc/articles/PMC2359868/ /pubmed/18466544 Text en Copyright © 2007 Gong et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an open access article distributed under the terms of the Creative Commons Attribution License ( (http://creativecommons.org/licenses/by/2.0) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Proceedings Gong, Bin-Sheng Zhang, Qing-Pu Zhang, Guang-Mei Zhang, Shao-Jun Zhang, Wei Lv, Hong-Chao Zhang, Fan Lv, Sa-Li Li, Chuan-Xing Rao, Shao-Qi Li, Xia Single-nucleotide polymorphism-gene intermixed networking reveals co-linkers connected to multiple gene expression phenotypes |
title | Single-nucleotide polymorphism-gene intermixed networking reveals co-linkers connected to multiple gene expression phenotypes |
title_full | Single-nucleotide polymorphism-gene intermixed networking reveals co-linkers connected to multiple gene expression phenotypes |
title_fullStr | Single-nucleotide polymorphism-gene intermixed networking reveals co-linkers connected to multiple gene expression phenotypes |
title_full_unstemmed | Single-nucleotide polymorphism-gene intermixed networking reveals co-linkers connected to multiple gene expression phenotypes |
title_short | Single-nucleotide polymorphism-gene intermixed networking reveals co-linkers connected to multiple gene expression phenotypes |
title_sort | single-nucleotide polymorphism-gene intermixed networking reveals co-linkers connected to multiple gene expression phenotypes |
topic | Proceedings |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2359868/ https://www.ncbi.nlm.nih.gov/pubmed/18466544 |
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